This invention relates to the field of digital image processing, and more particularly to methods for reducing noise and blocking artifacts in a digital image.
Digital images are widely used in image communication. Due to the various components in the image communication chain, along with various image processing methods applied to the digital images, these digital images may contain certain artifacts, such as imaging noise and JPEG blocking artifacts (if the image is highly compressed in a JPEG format). Thus, effective image enhancement techniques are required to process these digital images in order to achieve better image quality.
A typical approach known in the prior art for such image enhancement may comprise a series of sequential steps, such as the following:
1. noise reduction for a luminance channel through image filtering (e.g., as described in commonly assigned U.S. patent application Ser. No. 09/522,742, entitled xe2x80x9cNoise reduction method utilizing statistical weighting, apparatus, and program for digital image processingxe2x80x9d, filed Mar. 10, 2000 in the names of E. B. Gindele and J. Luo);
2. noise reduction for a chrominance channel through image filtering (e.g., as described in commonly assigned U.S. patent application Ser. No. 09/415,374, entitled xe2x80x9cRemoving chroma noise from digital images by variable shape pixel neighborhood regionsxe2x80x9d filed Oct. 8, 1999 in the names of J. E. Adams, Jr. and J. F. Hamilton, Jr.); and
3. JPEG de-blocking through image filtering (e.g., as described in H. C. Reeve III and J. S. Lim, xe2x80x9cReduction of blocking effect in image coding,xe2x80x9d ICASSP, pp. 1212-1215, 1983).
The main drawbacks of such sequential processing are the following:
1. output images are soft with severe loss of details due to consecutive filtering operations (i.e., smoothing in nature); and
2. execution speed is slow, and thus may not be suitable for time-critical applications.
In J. Luo et al, xe2x80x9cArtifact Reduction in Low Bit Rate DCT-based Image Compressionxe2x80x9d, IEEE Transaction on Image Processing, vol. 5, No. 9, September, 1996, Luo et al teaches a method for artifact reduction for JPEG compressed images by using a Huber-Markov random-field model-based filtering technique, which differentiates artifacts (e.g., noise and JPEG block boundaries) from image details and applies filtering that treats block boundaries and non-block boundaries differently.
This method for artifact reduction taught by Luo et al is based on a number of assumptions, such as:
1. image noise is not intensity dependent;
2. JPEG block boundary locations are known in advance; and
3. the input signal is a gray scale digital image.
These assumptions, however, may not hold for certain image applications. For example, images from most digital cameras are color images that have three channels (R, G, B). Moreover, for most digital cameras, noise level is highly intensity dependent. In addition, there will be no prior knowledge as to where the block boundaries are located if a cropping operation has been performed on the JPEG compressed images.
Therefore, it is highly desirable to develop an efficient algorithm that adaptively removes noise and JPEG blocking artifacts at the same time. Thus there is a need for an improved, efficient method for processing an image in order to reduce noise and blocking artifacts.
The present invention is directed to overcoming one or more of the problems set forth above. Briefly summarized, according to one aspect of the present invention, a digital image processing method reduces noise and blocking artifacts in a digital image having pixels representing RGB values by converting the digital image pixels to X1, X2 and X3 components; detecting the block boundaries in the X1, X2 and X3 image components; estimating the noise in the X1, X2 and X3 image components; constructing one or more noise tables for the X1, X2 and X3 image components; applying an adaptive Huber-Markov random-field model-based filter (HMRF) to the X1, X2 and X3 image components, where the HMRF employing the detected block boundaries and the noise tables to produce filtered X1, X2 and X3 image components; and converting the filtered X1, X2 and X3 image components to RGB components.
The present invention has the advantage that the amount of noise reduction applied is adapted to the local intensity and noise statistics of the digital image, resulting in a consistent-appearing image. The present invention also has the advantage that it does not require prior knowledge as to where the JPEG block boundaries are located.